Data Games

Data games are games that use real-world information for creating their content. Data is incorporated into game content under the assumption that players should view, learn and interact with such data during gameplay. However, data in its raw form is usually not suitable for direct use in-game, and need to be transformed. Transformation of data into content apt for gameplay includes data selection (i.e. selecting which parts of the data are useful to content generation) and structural transformation (i.e. adapting the data in accordance to the game).

Map generation for FreeCiv

This work investigates how to incorporate real-world data into game content so that the content is playable and enjoyable while not misrepresenting the data. We propose a method for generating balanced Civilization maps based on Open Data, describing how to acquire, transform and integrate information from different sources into a single content. Furthermore, we evolve playersí initial positions in order to obtain balanced maps, while trying to minimize information accuracy loss. In addition, this paper describes a tool to assist users in this process. Maps generated using these method and tool are playable and balanced yet faithful to the original sources.

Open Data Monopoly

With increasing amounts of open data, especially where data can be connected with various additional information resources, new ways of visualizing and making sense of this data become possible and necessary. This paper proposes, discusses and exemplifies the concept of data games, games that allow the player(s) to explore data that is derived from outside the game, by transforming the data into something that can be played with. The transformation takes the form of procedural content generation based on real-world data. As an example of a data game, this work describes Open Data Monopoly, a game board generator that uses economic and social indicator data for local governments in the UK. Game boards are generated by first collecting user input on which indicators to use and how to weigh them, as well as what criteria should be used for street selection. Sets of streets are then evolved that maximize the selected criteria, and ordered according to ìprosperityî as defined subjectively by the user. Chance and community cards are created based on auxiliary data about the local political entities.

Open Trumps

Open Trumps is a version of the popular card game Top Trumps with decks that are procedurally generated based on open data. The game is played among multiple players through drawing cards and selecting the feature that is most likely to trump the same feature on the other players' cards. Players can generate their own decks through choosing a suitable dataset and setting certain attributes; the generator then generates a balanced and playable deck using evolutionary computation. In the example dataset, each card represents a country and the features represent such entities as GDP per capita, mortality rate or tomato production, but in principle any dataset organised as instances with numerical features could be used. We also report the results of an evaluation intended to investigate both player experience and the hypothesis that players learn about the data underlying the deck they play with, since understanding the data is key to playing well. The results show that players enjoy playing the game, are enthusiastic about its potential and answer questions related to
decks they have played signicantly better than questions related to decks they have not played.

Bar Chart Ball

This work describes Bar Chart Ball, a game where players indirectly control a ball by modifying a bar chart that the ball rests on. The bar chart displays real-world demographic data about the UK, and the player modi es the chart by selecting which aspect of the data to focus on. By making data selection a core game mechanic, in fact the only game mechanic, we advance a novel and simple way of building game content from data, and of making data visualisation playable.